Automation is Getting a Kick in the Pants from A.I.

Security continues to be a major pain point for businesses of all shapes and sizes, and with the overwhelming volume of new and emerging threats hitting the scene on a daily basis, many professionals have turned to automated solutions based around artificial intelligence to fight back. While this presents a considerable benefit, it also creates other issues that need to be addressed if we want to take advantage of it in the years to come. Is there a way to use A.I. for network security without putting your business at risk?

To get the most out of A.I., we first need to understand why A.I. seems to be the likely answer to a lot of troubles surrounding network security.

What Makes A.I. So Helpful?
Automated systems might be able to help organizations protect a network to a certain degree, but there are a lot of reasons to be cautiously optimistic about their inclusion in modern network security. Considering the lack of technology education in today’s business environment, it can be difficult to acquire the skills needed to protect against high-level threats and implement necessary security solutions. This doesn’t change the fact that security is more important than ever before, though, as more devices are being introduced to networks every day. The more devices, the more likely threats are to surface, and the more difficult it is to protect networks. A.I., backed by algorithms to detect threats, has the potential to improve network security, as well as make the jobs of internal IT departments much easier.

Of course, there are several reasons why A.I. for network security isn’t the best solution. Here are a few of them.

Considering How Threats Are Detected by Artificial Intelligence
How does A.I. detect threats? Even if machine learning gives these solutions the ability to learn over time, it has to start somewhere. A.I. initially identifies threats based on algorithms assigned to them. According to the MIT Technology Review, A.I. is essentially “trained” to detect threats based on tags assigned to specific data sets. The unfortunate side-effect of this is that the programs can essentially be reverse-engineered by hackers if they get ahold of them, effectively giving malware developers the ability to create threats that aren’t identifiable by the majority of automated systems.

Overreliance on a Single Method
With only one way to detect threats, A.I. is quite vulnerable to being exploited, as hackers can simply turn that into their own advantage. This is why it’s so important to have multiple algorithms to detect threats, as only one isn’t going to be enough to keep all threats out of your network. Consider this hypothetical scenario: your office hires a single security guard that keeps watch over the front door of your building. There are no other guards on-site to protect the building, and you don’t have security cameras. While nobody is getting in the front door, what about the other entry points? It’s a simple fact that one algorithm is easily exploitable and far from an ideal security situation.

XFER can help your business determine the best security solutions on the market, and they can be combined with our expertise and active monitoring to ensure data security from a variety of threats. To learn more, reach out to us at 734-927-6666 / 800-GET-XFER.